SWI/SNF: Complex complexes in genome stability and cancer

Ribeiro-Silva, Cristina; Vermeulen, Wim; Lans, Hannes

doi:10.1016/j.dnarep.2019.03.007

Cited by 81 publications

(73 citation statements)

References 104 publications

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“…SWI/SNF complexes play a critical role in coordinating chromatin architecture and gene expression. They alter the structure of reconstituted chromatin particles in an ATP-dependent manner and make chromatin more accessible for transcription factor binding [44]. This is of particular interest since several families with multiple meningiomas and schwannomas harbor germline mutations in the SWI/SNF core complex unit SMARCB1.…”

Section: Discussionmentioning

confidence: 99%

“…Less frequent, sporadic mutations occur in WHO°I and WHO°II meningiomas concurrently with NF2 mutations and are associated with poorer prognosis [52]. Moreover, mutation in SMARCB1 are typically found in rhabdoid tumors and epithelioid sarcomas [44]. Even more rarely, a SMARCA4 mutation has been reported in one anaplastic meningioma [11].…”

Section: Discussionmentioning

confidence: 99%

“…Even more rarely, a SMARCA4 mutation has been reported in one anaplastic meningioma [11]. Taken together, members of the SWI/SNF complex may play a role in the pathogenesis of aggressive IVMs [11, 44].…”

Section: Discussionmentioning

confidence: 99%

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Intraventricular meningiomas frequently harbor NF2 mutations but lack common genetic alterations in TRAF7, AKT1, SMO, KLF4, PIK3CA, and TERT

Jungwirth

Warta

Beynon

et al. 2019

acta neuropathol commun

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Intraventricular meningiomas (IVMs) account for less than 5% of all intracranial meningiomas; hence their molecular phenotype remains unknown. In this study, we were interested whether genetic alterations in IVMs differ from meningiomas in other locations and analyzed our institutional series with respect to clinical and molecular characteristics. A total of 25 patients with surgical removal of an IVM at our department between 1986 and 2018 were identified from our institutional database. Median progression-free survival (PFS) was 79 months (range of 2–319 months) and PFS at 5 years was 86%. Corresponding tumor tissue was available for 18 patients including one matching recurrence and was subjected to targeted panel sequencing of 130 selected genes frequently mutated in brain cancers by applying a custom hybrid capture approach on a NextSeq500 instrument. Loss of chromosome 22q and 1p occurred frequently in 89 and 44% of cases. Deleterious NF2 mutations were found in 44% of IVMs ( n = 8/18). In non-NF2-mutated IVMs, previously reported genetic alterations including TRAF7, AKT1, SMO, KLF4, PIK3CA, and TERT were lacking, suggesting alternative genes in the pathogenesis of non-NF2 IVMs. In silico analysis revealed possible damaging mutations of APC, GABRA6, GSE1, KDR, and two SMO missense mutations differing from previously reported ones. Interestingly, all WHO°II IVMs ( n = 3) harbored SMARCB1 and SMARCA4 mutations, indicating a role of the SWI/SNF chromatin remodeling complex in aggressive IVMs. Electronic supplementary material The online version of this article (10.1186/s40478-019-0793-4) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Intraventricular meningiomas frequently harbor NF2 mutations but lack common genetic alterations in TRAF7, AKT1, SMO, KLF4, PIK3CA, and TERT

Jungwirth

Warta

Beynon

et al. 2019

acta neuropathol commun

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“…Beyond these functions at the level of oncogenic signalling, the BAF complex is pivotal in maintaining genome integrity [60]. This may happen via different routes.…”

Section: Three Of a Kind? Structure And Functions Of Three Baf Complexesmentioning

confidence: 99%

Invited Review: Dysregulation of chromatin remodellers in paediatric brain tumours – SMARCB1 and beyond

Johann

2020

Neuropathology Appl Neurobio

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2020) Neuropathology and Applied Neurobiology 46, 57-72 Dysregulation of chromatin remodellers in paediatric brain tumours -SMARCB1 and beyond Mutations in chromatin remodelling genes occur in approximately 25% of all human tumours (Kadoch et al. Nat Genet 45: 592-601, 2013). The spectrum of alterations is broad and comprises single nucleotide variants, insertion/deletions and more complex structural variations. The single most often affected remodelling complex is the SWI/SNF complex (SWItch/sucrose non-fermentable). In the field of paediatric neuro-oncology, the spectrum of affected genes implicated in epigenetic remodelling is narrower with SMARCB1 and SMARCA4 being the most frequent.The low mutation frequencies in many of the SWI/SNF mutant entities underline the fact that perturbed chromatin remodelling is the most salient factor in tumourigenesis and could thus be a potential therapeutic opportunity. Here, I review the genetic basis of aberrant chromatin remodelling in paediatric brain tumours and discuss their impact on the epigenome in the respective entities, mainly medulloblastomas and rhabdoid tumours. Aberrations described in-Rhabdoid tumours eletions/SNVs (95% of all cases) -rare entities: INI1 deficient chordomas (10-20% of all cases), CRINET (all cases) Figure 1. An overview on SWItch/sucrose non-fermentable aberrant paediatric entities. CRINET, cribriform neuroepithelial tumours. Dysregulation of chromatin remodellers in paediatric neurooncology 61 CNS CRINET Point mutations CNS CRINET, cribriform neuroepithelial tumours.

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“…For the combination of DASATINIB and ABT-888 in MSTO-211H, besides BCRABL-BMI interaction mentioned before, SNF5 pathway is also ranked on the top. It worth mentioning that both SNF5 and PARP1/2 play key roles in the DNA repair process (Javle and Curtin, 2011;Ribeiro-Silva, et al, 2019).…”

Section: Shapley Additive Gene Set Enrichment Analysis Reveals Novel mentioning

confidence: 99%

TranSynergy: Mechanism-Driven Interpretable Deep Neural Network for the Synergistic Prediction and Pathway Deconvolution of Drug Combinations

Qiao

Xie

2020

Preprint

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Motivation: Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. With the fast-growing number of anti-cancer drugs, the experimental investigation of all drug combinations is costly and time-consuming. Computational techniques can improve the efficiency of drug combination screening. Despite recent advances in applying machine learning to synergistic drug combinations prediction, several challenges remain. First, the performance of existing methods is suboptimal. There is still much space for improvement. Second, biological knowledge has not been fully incorporated into the model. Finally, many models are lack of interpretability, limiting their clinical applications. Results: We develop a knowledge-enabled and self-attention boosted deep learning model, TranSynergy, to improve the performance and interpretability of synergistic drug combinations prediction. TranSynergy is well designed such that cellular effect of drug actions can be explicitly modeled through cell-line gene dependency, gene-gene interaction, and genome-wide drug-target interaction. A novel Shapley Additive Gene Set Enrichment Analysis (SA-GSEA) method is developed to deconvolute biological pathways that contribute to the synergistic drug combination and improve model interpretability. Extensive benchmark studies demonstrate that TranSynergy significantly outperforms the state-of-the-art method, suggesting the potential of mechanism-driven machine learning. Novel pathways that are associated with the synergistic combinations are revealed and supported by experimental evidence. They may provide new insights into identifying biomarkers for precision medicine and discovering new anti-cancer therapies. Several new synergistic drug combinations are predicted with high confidence for ovarian cancer which has few treatment options. Availability: The code is available at https://github.com/qiaoliuhub/drug_combination

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SWI/SNF: Complex complexes in genome stability and cancer

Cited by 81 publications

References 104 publications

Intraventricular meningiomas frequently harbor NF2 mutations but lack common genetic alterations in TRAF7, AKT1, SMO, KLF4, PIK3CA, and TERT

Intraventricular meningiomas frequently harbor NF2 mutations but lack common genetic alterations in TRAF7, AKT1, SMO, KLF4, PIK3CA, and TERT

Invited Review: Dysregulation of chromatin remodellers in paediatric brain tumours – SMARCB1 and beyond

TranSynergy: Mechanism-Driven Interpretable Deep Neural Network for the Synergistic Prediction and Pathway Deconvolution of Drug Combinations

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